Merge pull request #39 from quantopian/fawce_sprint3

Fawce sprint3

zipline/finance/performance.py

@@ -40,9 +40,12 @@ Performance Tracking
     |                 | through all the events delivered to this tracker.  |
     |                 | For details look at the comments for               |
     |                 | :py:meth:`zipline.finance.risk.RiskMetrics.to_dict`|
+    +-----------------+----------------------------------------------------+ 
+    | exceeded_max_   | True if the simulation was stopped because single  | 
+    | loss            | day losses exceeded the max_drawdown stipulated in |
+    |                 | trading_environment.                               |
     +-----------------+----------------------------------------------------+
 
-
 Position Tracking
 =================
 
@@ -154,6 +157,7 @@ class PerformanceTracker():
         self.result_stream           = None
         self.last_dict               = None
         self.order_log               = []
+        self.exceeded_max_loss       = False
 
         # this performance period will span the entire simulation.
         self.cumulative_performance = PerformancePeriod(
@@ -213,7 +217,7 @@ class PerformanceTracker():
             'capital_base'            : self.capital_base,
             'cumulative_perf'         : self.cumulative_performance.to_dict(),
             'daily_perf'              : self.todays_performance.to_dict(),
-            'cumulative_risk_metrics' : self.cumulative_risk_metrics.to_dict(),
+            'cumulative_risk_metrics' : self.cumulative_risk_metrics.to_dict()  
         }
     
     def log_order(self, order):
@@ -263,11 +267,37 @@ class PerformanceTracker():
         # calculate progress of test
         self.progress = self.day_count / self.total_days
 
+        if self.trading_environment.max_drawdown:
+            max_dd = -1 * self.trading_environment.max_drawdown
+            if self.todays_performance.returns < max_dd:
+                qutil.LOGGER.info("Exceeded max drawdown.")
+                # mark the perf period with max loss flag, 
+                # so it shows up in the update, but don't end the test
+                # here. Let the update go out before stopping
+                self.exceeded_max_loss = True
+                
         # Output results
         if self.result_stream:
             msg = zp.PERF_FRAME(self.to_dict())
             self.result_stream.send(msg)
-
+            
+        if self.exceeded_max_loss:
+            # now that we've sent the day's update, kill this test
+            self.handle_simulation_end(skip_close=True)
+            return
+            
+        # check the day's returns versus the max drawdown
+        # max_drawdown is optional:
+        if self.trading_environment.max_drawdown:
+            max_dd = -1 * self.trading_environment.max_drawdown
+            if self.todays_performance.returns < max_dd:
+                qutil.LOGGER.info("Exceeded max drawdown.")
+                # TODO: any other information we need to relay on the 
+                # result socket?
+                self.exceeded_max_loss = True
+                self.handle_simulation_end(skip_close=True)
+                return
+            
         #move the market day markers forward
         self.market_open = self.market_open + self.calendar_day
 
@@ -288,7 +318,7 @@ class PerformanceTracker():
             keep_transactions = True
         )
 
-    def handle_simulation_end(self):
+    def handle_simulation_end(self, skip_close=False):
         """
         When the simulation is complete, run the full period risk report
         and send it out on the result_stream.
@@ -300,18 +330,21 @@ class PerformanceTracker():
         
         # the stream will end on the last trading day, but will not trigger
         # an end of day, so we trigger the final market close here.
-        self.handle_market_close()
-        
+        # In the case of errors, we needn't close again.
+        if not skip_close:
+            self.handle_market_close()
         
         self.risk_report = risk.RiskReport(
             self.returns,
-            self.trading_environment
+            self.trading_environment,
+            exceeded_max_loss = self.exceeded_max_loss
         )
-
+        
         if self.result_stream:
             qutil.LOGGER.info("about to stream the risk report...")
-            report = self.risk_report.to_dict()
-            msg = zp.RISK_FRAME(report)
+            risk_dict = self.risk_report.to_dict()
+            
+            msg = zp.RISK_FRAME(risk_dict)
             self.result_stream.send(msg)
             # this signals that the simulation is complete.
             self.result_stream.send("DONE")

zipline/finance/risk.py

@@ -315,7 +315,11 @@ class RiskMetrics():
 
 class RiskReport():
 
-    def __init__(self, algorithm_returns, trading_environment):
+    def __init__(
+        self, 
+        algorithm_returns, 
+        trading_environment, 
+        exceeded_max_loss=False):
         """
         algorithm_returns needs to be a list of daily_return objects
         sorted in date ascending order
@@ -323,6 +327,7 @@ class RiskReport():
 
         self.algorithm_returns = algorithm_returns
         self.trading_environment = trading_environment
+        self.exceeded_max_loss = exceeded_max_loss
 
         if len(self.algorithm_returns) == 0:
             start_date = self.trading_environment.period_start
@@ -352,10 +357,11 @@ class RiskReport():
         provided for each period.
         """
         return {
-            'one_month'     : [x.to_dict() for x in self.month_periods],
-            'three_month'   : [x.to_dict() for x in self.three_month_periods],
-            'six_month'     : [x.to_dict() for x in self.six_month_periods],
-            'twelve_month'  : [x.to_dict() for x in self.year_periods]
+            'one_month'         : [x.to_dict() for x in self.month_periods],
+            'three_month'       : [x.to_dict() for x in self.three_month_periods],
+            'six_month'         : [x.to_dict() for x in self.six_month_periods],
+            'twelve_month'      : [x.to_dict() for x in self.year_periods],
+            'exceeded_max_loss' : self.exceeded_max_loss
         }
 
     def periodsInRange(self, months_per, start, end):

zipline/finance/trading.py

@@ -99,6 +99,10 @@ class TradeSimulationClient(qmsg.Component):
 
     def process_event(self, event):
         
+        if self.perf.exceeded_max_loss:
+            self.control_out.send(str(zp.CONTROL_PROTOCOL.SHUTDOWN))
+            return
+            
         # generate transactions, if applicable
         txn = self.txn_sim.apply_trade_to_open_orders(event)
         if txn:

zipline/protocol.py

@@ -663,6 +663,7 @@ def convert_transactions(transactions):
     for txn in transactions:
         txn['date'] = EPOCH(txn['dt'])
         del(txn['dt'])
+        del(txn['source_id'])
         results.append(txn)
     return results